Green human resource management and green supply Chain Management on Sustainable performance of nickel mining companies in Indonesia
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The green economy with Islamic perspective is the primary discussion point in this study since it is seen as a potential solution to the current economic and environmental concerns. This study aims to analyze the Sustainability Performance of a nickel mine in North Maluku using Islamic economic perspective. A total of 80 mining workers in North Maluku were respondents in the study who were selected using the convenience sampling method. The results of data processing using structural equation modeling show that five of the six proposed hypotheses are empirically proven, the findings in this study indicate that the Sustainability Performance of nickel mining companies in North Maluku can be achieved through the practice of Green Human Resource Management which forms Health, Safety, Environmental Culture, and Green Supply Chain Management practices. The managerial implication of the findings in this study is that mining companies in North Maluku pay attention to recruitment supervision, training, and impose a system of rewards and punishments for workers related to safe work behavior and environmental preservation. In addition, the company also reports holding regular meetings with workers to socialize company policies related to work safety and environmental preservation. Finally, a license to carry out ISO certification to support the implementation of a supply chain that is environmentally sound and to have and carry out environmental program audits and support environmental-related regulations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it